Publications

Publications

Original SeLECT

In this first study, we developed and validated the SeLECT score, an innovative prognostic tool for predicting the risk of late seizures after ischemic stroke. Using five easily obtainable clinical variables—stroke severity, large-artery atherosclerosis, early seizures, cortical involvement, and middle cerebral artery involvement—we demonstrated high predictive accuracy across multiple international cohorts.

Thrombolysis

Building on our initial development of the SeLECT score, we further investigated the role of thrombolysis and reperfusion therapies in the context of seizure risk after ischemic stroke. This subsequent study demonstrated that while reperfusion treatments such as intravenous thrombolysis and thrombectomy are essential for reducing stroke-related disability, they do not independently increase the risk of late seizures when accounting for stroke severity and cortical involvement.

SeLECT 2.0

In this study, we examined the impact of acute symptomatic seizures, particularly status epilepticus, on long-term outcomes after ischemic stroke. Our findings revealed that patients with status epilepticus face significantly higher risks of mortality and post-stroke epilepsy. Building on these insights, we adapted the SeLECT score to incorporate status epilepticus, enhancing its predictive accuracy for post-stroke seizure risk.

Driving

In this study, we investigated how the SeLECT2.0 score can guide safe driving decisions for stroke survivors at risk of seizures. By quantifying the conditional seizure risk (COSY) based on individual stroke characteristics and seizure-free intervals (SFI), we identified personalized thresholds for private and professional driving safety. Our findings revealed that COSY below 20% for private driving is achievable immediately in low-risk individuals (SeLECT2.0 scores 0–7), while higher-risk individuals may require SFIs of 5–20 months depending on their baseline score.

Preprints

SeLECT-ASyS

In this study, we examined how the timing and type of acute symptomatic seizures (ASyS) following ischemic stroke influence the risk of developing post-stroke epilepsy and mortality. By analyzing a large multicenter cohort of 4,552 stroke survivors, we demonstrated that ASyS occurring on the day of stroke onset (day 0) and seizures presenting as status epilepticus or focal to bilateral tonic-clonic seizures were associated with the highest risks. Using these insights, we developed and validated the novel SeLECT-ASyS model, which significantly outperformed the previous SeLECT2.0 model in predicting post-stroke epilepsy risk for patients with ASyS.

SeLECT-EEG

In this study, we explored the role of early electrographic biomarkers detected through EEG in predicting post-stroke epilepsy and developed a novel prognostic model, SeLECT-EEG, to improve risk estimation. By analyzing data from 1,105 stroke survivors who underwent EEG within seven days of acute ischemic stroke, we identified specific biomarkers, including epileptiform activity and regional slowing, as significant predictors of post-stroke epilepsy. The SeLECT-EEG model demonstrated superior predictive accuracy compared to the prior SeLECT2.0 model, particularly in patients without acute symptomatic seizures. Our findings revealed that patients with epileptiform activity had a 42% 5-year risk of post-stroke epilepsy, while those without showed a significantly lower risk (13%).

Orginal SeLECT

Title & Abstract

Prediction of late seizures after ischaemic stroke with a novel prognostic model (the SeLECT score): a multivariable prediction model development and validation study

Background

Stroke is one of the leading causes of acquired epilepsy in adults. An instrument to predict whether people are at high risk of developing post-stroke seizures is not available. We aimed to develop and validate a prognostic model of late (>7 days) seizures after ischaemic stroke.

Methods

In this multivariable prediction model development and validation study, we developed the SeLECT score based on five clinical predictors in 1200 participants who had an ischaemic stroke in Switzerland using backward elimination of a multivariable Cox proportional hazards model. We externally validated this score in 1169 participants from three independent international cohorts in Austria, Germany, and Italy, and assessed its performance with the concordance statistic and calibration plots.

Findings

Data were complete for 99·2% of the predictors (99·2% for Switzerland, 100% for Austria, 97% for Germany, and 99·7% for Italy) and 100% of the outcome parameters. Overall, the risk of late seizures was 4% (95% CI 4–5) 1 year after stroke and 8% (6–9) 5 years after stroke. The final model included five variables and was named SeLECT on the basis of the first letters of the included parameters (severity of stroke, large-artery atherosclerotic aetiology, early seizures, cortical involvement, and territory of middle cerebral artery involvement). The lowest SeLECT value (0 points) was associated with a 0·7% (95% CI 0·4–1·0) risk of late seizures within 1 year after stroke (1·3% [95% CI 0·7–1·8] within 5 years), whereas the highest value (9 points) predicted a 63% (42–77) risk of late seizures within 1 year (83% [62–93] within 5 years). The model had an overall concordance statistic of 0·77 (95% CI 0·71–0·82) in the validation cohorts. Calibration plots indicated high agreement of predicted and observed outcomes.

Interpretation

This easily applied instrument was shown to be a good predictor of the risk of late seizures after stroke in three external validation cohorts and is freely available as a smartphone app. The SeLECT score has the potential to identify individuals at high risk of seizures and is a step towards more personalised medicine. It can inform the selection of an enriched population for antiepileptogenic treatment trials and will guide the recruitment for biomarker studies of epileptogenesis

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Main Figure

Key Points

Objective:

  • Develop and validate the SeLECT score, a simple, practical tool to predict late seizures (>7 days) after ischemic stroke using routinely available clinical variables.

Methods:

  • Study Design:
    • Multivariable prediction model development and validation study.
    • Derivation cohort: 1200 patients from Switzerland.
    • Validation cohorts: 1169 patients across Austria, Germany, and Italy.
  • Predictive Variables:
    • The SeLECT score is based on five predictors:
      1. Severity of stroke (NIHSS score).
      2. Large-artery atherosclerosis as the stroke etiology.
      3. Early seizures within 7 days post-stroke.
      4. Cortical involvement on imaging.
      5. Middle cerebral artery (MCA) territory involvement.
  • Scoring System:
    • Each variable is assigned weighted points, with a total score ranging from 0 to 9.

Findings:

  • Risk Prediction:
    • 1-year seizure risk:
      • 0 points: 0.7% risk (95% CI: 0.4–1.0).
      • 9 points: 63% risk (95% CI: 42–77).
    • 5-year seizure risk:
      • 0 points: 1.3% risk (95% CI: 0.7–1.8).
      • 9 points: 83% risk (95% CI: 62–93).
  • Model Accuracy:
    • Overall concordance statistic (C-statistic): 0.77 (95% CI: 0.71–0.82) across validation cohorts.
    • High calibration between predicted and observed risks.

Clinical Implications:

  • The SeLECT score provides individualized seizure risk estimates for stroke survivors.
  • Supports personalized patient care, risk stratification, and future antiepileptogenic treatment trials.
  • Freely available as a smartphone application for easy use in clinical settings.

Conclusion:

  • The SeLECT score is a validated, user-friendly tool for predicting post-stroke seizures, facilitating personalized care and advancing research into post-stroke epilepsy.

Thrombolysis

Title & Abstract

Seizures after Ischemic Stroke: A Matched Multicenter Study

Objective

The purpose of this study was to identify risk factors for acute symptomatic seizures and post-stroke epilepsy after acute ischemic stroke and evaluate the effects of reperfusion treatment.

Methods

We assessed the risk factors for post-stroke seizures using logistic or Cox regression in a multicenter study, including adults from 8 European referral centers with neuroimaging-confirmed ischemic stroke. We compared the risk of post-stroke seizures between participants with or without reperfusion treatment following propensity score matching to reduce confounding due to treatment selection.

Results

In the overall cohort of 4,229 participants (mean age 71 years, 57% men), a higher risk of acute symptomatic seizures was observed in those with more severe strokes, infarcts located in the posterior cerebral artery territory, and strokes caused by large-artery atherosclerosis. Strokes caused by small-vessel occlusion carried a small risk of acute symptomatic seizures. 6% developed post-stroke epilepsy. Risk factors for post-stroke epilepsy were acute symptomatic seizures, more severe strokes, infarcts involving the cerebral cortex, and strokes caused by large-artery atherosclerosis. Electroencephalography findings within 7 days of stroke onset were not independently associated with the risk of post-stroke epilepsy. There was no association between reperfusion treatments in general or only intravenous thrombolysis or mechanical thrombectomy with the time to post-stroke epilepsy or the risk of acute symptomatic seizures.

Interpretation

Post-stroke seizures are related to stroke severity, etiology, and location, whereas an early electroencephalogram was not predictive of epilepsy. We did not find an association of reperfusion treatment with risks of acute symptomatic seizures or post-stroke epilepsy.

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Main Figure

Key Points

Objectives:

  • To identify risk factors for acute symptomatic seizures (ASS) and post-stroke epilepsy (PSE) after ischemic stroke.
  • To evaluate the impact of reperfusion treatments (IV thrombolysis, mechanical thrombectomy) on seizure risk.

Key Findings:

  1. Risk Factors:

    • Acute symptomatic seizures were linked to severe strokes (NIHSS ≥11), cortical involvement, posterior cerebral artery territory infarcts, and large-artery atherosclerosis.
    • The strongest predictor of post-stroke epilepsy was the occurrence of acute symptomatic seizures.

  2. Reperfusion Treatments:

    • Reperfusion treatments were initially associated with a higher seizure risk in univariable analysis but showed no independent association after adjusting for stroke severity and location.
    • Time to thrombolysis and successful recanalization did not influence the risk of seizures or post-stroke epilepsy.

  3. Role of EEG:

    • Abnormal findings in early EEGs were not independently predictive of post-stroke epilepsy after adjusting for clinical covariates.

Clinical Implications:

  • Acute symptomatic seizures indicate a heightened risk for post-stroke epilepsy, emphasizing the need for close monitoring and personalized management.
  • Reperfusion therapies remain safe concerning seizure risk, reinforcing their use in eligible stroke patients.
  • Early EEG findings alone should not guide epilepsy risk assessments but may complement other clinical data.

SeLECT 2.0

Title & Abstract

Association of Mortality and Risk of Epilepsy With Type of Acute Symptomatic Seizure After Ischemic Stroke and an Updated Prognostic Model

Importance

Acute symptomatic seizures occurring within 7 days after ischemic stroke may be associated with an increased mortality and risk of epilepsy. It is unknown whether the type of acute symptomatic seizure influences this risk.

Objective

To compare mortality and risk of epilepsy following different types of acute symptomatic seizures.

Design, setting, and participants

This cohort study analyzed data acquired from 2002 to 2019 from 9 tertiary referral centers. The derivation cohort included adults from 7 cohorts and 2 case-control studies with neuroimaging-confirmed ischemic stroke and without a history of seizures. Replication in 3 separate cohorts included adults with acute symptomatic status epilepticus after neuroimaging-confirmed ischemic stroke. The final data analysis was performed in July 2022.

Exposures

Type of acute symptomatic seizure.

Main outcomes and measures

All-cause mortality and epilepsy (at least 1 unprovoked seizure presenting >7 days after stroke).

Results

A total of 4552 adults were included in the derivation cohort (2547 male participants [56%]; 2005 female [44%]; median age, 73 years [IQR, 62-81]). Acute symptomatic seizures occurred in 226 individuals (5%), of whom 8 (0.2%) presented with status epilepticus. In patients with acute symptomatic status epilepticus, 10-year mortality was 79% compared with 30% in those with short acute symptomatic seizures and 11% in those without seizures. The 10-year risk of epilepsy in stroke survivors with acute symptomatic status epilepticus was 81%, compared with 40% in survivors with short acute symptomatic seizures and 13% in survivors without seizures. In a replication cohort of 39 individuals with acute symptomatic status epilepticus after ischemic stroke (24 female; median age, 78 years), the 10-year risk of mortality and epilepsy was 76% and 88%, respectively. We updated a previously described prognostic model (SeLECT 2.0) with the type of acute symptomatic seizures as a covariate. SeLECT 2.0 successfully captured cases at high risk of poststroke epilepsy.

Conclusions and relevance

In this study, individuals with stroke and acute symptomatic seizures presenting as status epilepticus had a higher mortality and risk of epilepsy compared with those with short acute symptomatic seizures or no seizures. The SeLECT 2.0 prognostic model adequately reflected the risk of epilepsy in high-risk cases and may inform decisions on the continuation of antiseizure medication treatment and the methods and frequency of follow-up.

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Main Figure

Key Points

Key Findings:

  • Incidence of ASS and Status Epilepticus (SE):

    • Among 4,552 patients, 5% experienced ASS, with 0.2% presenting as SE.

  • Mortality Rates:

    • 10-year mortality was highest in patients with ASS presenting as SE (79%), compared to those with short seizures (30%) and without ASS (11%).

  • Risk of Developing PSE:

    • Stroke survivors with ASS presenting as SE had an 81% risk of developing PSE within 10 years, significantly higher than those with short seizures (40%) and without ASS (13%).

Clinical Implications:

  • Prognostic Significance of SE:

    • ASS manifesting as SE is a strong predictor of both increased mortality and higher risk of PSE, underscoring the need for vigilant monitoring and management in these patients.

  • Updated SeLECT 2.0 Score:

    • Incorporating the type of ASS into the SeLECT score (now SeLECT 2.0) enhances its predictive accuracy for PSE, aiding clinicians in stratifying risk and tailoring follow-up strategies.

Conclusion:

The study emphasizes the critical impact of ASS, particularly when presenting as SE, on long-term outcomes after ischemic stroke. The updated SeLECT 2.0 model serves as a valuable tool for predicting PSE risk, facilitating informed clinical decisions regarding patient management and follow-up.

Driving

Title & Abstract

Implications for driving based on the risk of seizures after ischaemic stroke

Background

In addition to other stroke-related deficits, the risk of seizures may impact driving ability after stroke.

Methods

We analysed data from a multicentre international cohort, including 4452 adults with acute ischaemic stroke and no prior seizures. We calculated the Chance of Occurrence of Seizure in the next Year (COSY) according to the SeLECT2.0 prognostic model. We considered COSY<20% safe for private and <2% for professional driving, aligning with commonly used cut-offs.

Results

Seizure risks in the next year were mainly influenced by the baseline risk-stratified according to the SeLECT2.0 score and, to a lesser extent, by the poststroke seizure-free interval (SFI). Those without acute symptomatic seizures (SeLECT2.0 0–6 points) had low COSY (0.7%–11%) immediately after stroke, not requiring an SFI. In stroke survivors with acute symptomatic seizures (SeLECT2.0 3–13 points), COSY after a 3-month SFI ranged from 2% to 92%, showing substantial interindividual variability. Stroke survivors with acute symptomatic status epilepticus (SeLECT2.0 7–13 points) had the highest risk (14%–92%).

Conclusions

Personalised prognostic models, such as SeLECT2.0, may offer better guidance for poststroke driving decisions than generic SFIs. Our findings provide practical tools, including a smartphone-based or web-based application, to assess seizure risks and determine appropriate SFIs for safe driving.

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Main Figure

Key Points

Objective:

To assess seizure risk after ischemic stroke using the SeLECT2.0 model, focusing on its implications for driving safety based on seizure-free intervals (SFI) and personalized risk estimates.

Key Findings:

  1. Risk Quantification:

    • The SeLECT2.0 score was used to predict the conditional risk of unprovoked seizures (COSY) over different SFIs.
    • COSY ranged from <1% (low risk) for SeLECT2.0 scores of 0-6 to over 90% (high risk) for scores of 13, depending on SFI.

  2. Driving Implications:

    • COSY <20% is considered safe for private driving, while <2% is required for professional driving.
    • Individuals with SeLECT2.0 scores of 0–6 had COSY <20% immediately, requiring no SFI for private driving.
    • Higher scores (7–13) required SFIs ranging from 5–20 months or longer to meet safe thresholds.

  3. Impact of Acute Symptomatic Seizures:

    • Patients with acute symptomatic status epilepticus (SeLECT2.0 score ≥7) had the highest seizure risk, often exceeding safety thresholds even after long SFIs.

  4. Model Accuracy:

    • The SeLECT2.0 model provided robust predictions validated across multiple international cohorts.

Clinical Implications:

  • SeLECT2.0 offers personalized seizure risk predictions, enabling more precise recommendations for driving eligibility after stroke.
  • The model challenges one-size-fits-all approaches by tailoring SFIs based on individual risk, balancing safety with quality of life.